Uwe Krüger

Organelle-based classification of metastatic breast cancer subtypes using self-supervised learning

Harrison J. Yee, Megan Bouyea, Joshua Goldwag, John M. Lamar et autres

A data fusion deep learning approach for accurate organelle-based classification of cancer cells

Harrison J. Yee, Megan Bouyea, Joshua Goldwag, John M. Lamar et autres

Purpose: Microscopy-based cancer cell classification traditionally relies on cell-based morphological features, while subcellular organelle organization remains underutilized. Existing machine learning methods often require manual preprocessing and handcrafted feature extraction, limiting scalability and introducing user bias. This study proposes an automated, interpretable, and …

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Editorial Criteria for TMI Papers—Significance, Innovation, Evaluation, and Reproducibility

Hongming Shan, Uwe Krüger, Ge Wang

IEEE Transactions on Medical Imaging (TMI) publishes high-quality work that innovates imaging methods and advances medicine, science, and engineering. While artificial intelligence (AI) is currently prominent, the journal's scope extends well beyond AI-based imaging to encompass a full spectrum of imaging methods …

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Deep learning-based cancer cell classification using morphological and topological organelle features

Harrison J. Yee, Megan Bouyea, Joshua Goldwag, John M. Lamar et autres

In the eld of cancer research, there has been a growing interest in understanding how variations in cell morphology contribute to cancer cell dynamics and phenotypes. Across dierent breast cancer cell lines, extensive phenotypic and morphologic heterogeneity has been observed primarily through …

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Dynamic directed functional connectivity as a neural biomarker for objective motor skill assessment

Anil Kamat, Rahul Rahul, Anirban Dutta, Lora Anne Cavuoto et autres

Objective motor skill assessment plays a critical role in fields such as surgery, where proficiency is vital for certification and patient safety. Existing assessment methods, however, rely heavily on subjective human judgment, which introduces bias and limits reproducibility. While recent efforts have …

Integrating AI in college education: Positive yet mixed experiences with ChatGPT

Xinrui Song, Jiajin Zhang, Pingkun Yan, Juergen Hahn et autres

The integration of artificial intelligence (AI) chatbots into higher education marks a shift towards a new generation of pedagogical tools, mirroring the arrival of milestones like the internet. With the launch of ChatGPT-4 Turbo in November 2023, we developed a ChatGPT-based teaching …

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Integrating AI in College Education: Positive yet Mixed Experiences with ChatGPT

Xinrui Song, Jiajin Zhang, Pingkun Yan, Juergen Hahn et autres

The integration of artificial intelligence (AI) chatbots into higher education marks a shift towards a new generation of pedagogical tools, mirroring the arrival of milestones like the internet. With the launch of ChatGPT-4 Turbo in November 2023, we developed a ChatGPT-based teaching …

Mechanical behavior of full-thickness burn human skin is rate-independent

Samara Gallagher, Kartik Josyula, R. Rahul, Uwe Krüger et autres

Skin tissue is recognized to exhibit rate-dependent mechanical behavior under various loading conditions. Here, we report that the full-thickness burn human skin exhibits rate-independent behavior under uniaxial tensile loading conditions. Mechanical properties, namely, ultimate tensile stress, ultimate tensile strain, and toughness, and …

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Organelle-based breast cancer cell classification with deep learning and visual explanations

Harrison J. Yee, Kailie Matteson, Joshua Goldwag, John M. Lamar et autres

Breast cancer cell analysis has traditionally focused on cell and intracellular organelle morphology. Recent research has demonstrated that organelle topology-based cancer cell classification is considerably more accurate when using handcrafted feature extraction and machine learning-based classifiers on fluorescent confocal microscopy images. However, …

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Organelle Topology Profiling of Metastatic Cancer Cells Using Machine Learning Classification

Fatma Awadalla, Dancan Oruko, Joshua Goldwag, Kailie Matteson et autres

Organelle Topology-based Cell Classification Pipeline can discriminate between metastatic cell lines with very high accuracy (>90%) using mitochondria or endosome immunolabeling, confocal microscopy and 3D rendering followed by several machine learning classifiers.

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SENSITIVITY EVALUATION OF MEASUREMENT UNCERTAINTY CONTRIBUTIONS OF SPECTRAL DATA FOR CALCULATED INTEGRAL QUANTITIES

Uwe Krüger, J. Dubard, Erkki Ikonen, Armin Sperling et autres

Integrating spectral data (spectral responsivities of photometers or spectral distributions of light sources) to calculate quantities such as tristimulus values is straightforward at first sight. However, estimating the measurement uncertainty of these integrated quantities is challenging. When calculating integral photometric quantities, some …

Predicting Problematic Behavior in Autism Spectrum Disorder Using Medical History and Environmental Data

Jennifer Ferina, Melanie Krüger, Uwe Krüger, Daniel Ryan et autres

Autism spectrum disorder (ASD), characterized by social, communication, and behavioral abnormalities, affects 1 in 36 children according to the CDC. Several co-occurring conditions are often associated with ASD, including sleep and immune disorders and gastrointestinal (GI) problems. ASD is also associated with …

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